On the Least Absolute Deviations Method for Ridge Estimation of SURE Models
This paper examines the application of the Least Absolute Deviations (LAD) method for ridge-type parameter estimation of Seemingly Unrelated Regression Equations (SURE) models. The methodology is aimed to deal with the SURE models with non-Gaussian error terms and highly collinear predictors in each equation. Some biasing parameters used in the literature are taken and the efficiency of both Least Squares (LS) ridge estimation and the LAD ridge estimation of the SURE models, through the Mean Squared Error (MSE) of parameter estimators, is evaluated.
|Date of creation:||24 Oct 2012|
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- Shukur, Ghazi & Zeebari, Zangin, 2011. "On the median regression for SURE models with applications to 3-generation immigrants data in Sweden," Economic Modelling, Elsevier, vol. 28(6), pages 2566-2578.
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- Ekberg, Jan & Hammarstedt, Mats & Shukur, Ghazi, 2007. "SUR estimation of earnings differentials between three generations of immigrants and natives," CAFO Working Papers 2007:7, Centre for Labour Market Policy Research (CAFO), School of Business and Economics, Linnaeus University.
- Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
- Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
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